Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Enhancing Clinical Documentation Workflow with Ambient Artificial Intelligence: Clinician Perspectives on Work Burden, Burnout, and Job Satisfaction
9
Zitationen
9
Autoren
2024
Jahr
Abstract
ABSTRACT Objective This study assessed the effects of an ambient artificial intelligence (AI) documentation platform on clinicians’ perceptions of documentation workflow. Materials and Methods A pre- and post-implementation survey evaluated ambulatory clinician perceptions on impact of Abridge, an ambient AI documentation platform. Outcomes included clinical documentation burden, work after-hours, clinician burnout, work satisfaction, and patient access. Data were analyzed using descriptive statistics and proportional odds logistic regression to compare changes for concordant questions across pre- and post-surveys. Covariate analysis examined effect of specialty type and duration of use of the AI tool. Results Survey response rates were 51.1% (94/181) pre-implementation and 75.9% (101/133) post-implementation. Clinician perception of ease of documentation workflow (OR = 6.91, 95% CI: 3.90 to 12.56, p<0.001) and in completing notes associated with usage of the AI tool (OR = 4.95, 95% CI: 2.87 to 8.69, p<0.001) was significantly improved. The majority of respondents agreed that the AI tool decreased documentation burden, decreased the time spent documenting outside clinical hours, reduced burnout risk, and increased job satisfaction, with 48% agreeing that an additional patient could be seen if needed. Clinician specialty type and number of days using the AI tool did not significantly affect survey responses. Discussion Clinician experience and efficiency was dramatically improved with use of Abridge across a breadth of specialties. Conclusion An ambient AI documentation platform had tremendous impact on improving clinician experience within a short time frame. Future studies should utilize validated instruments for clinician efficiency and burnout and compare impact across AI platforms.
Ähnliche Arbeiten
Machine Learning in Medicine
2019 · 3.620 Zit.
Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care
2006 · 3.168 Zit.
Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes
2005 · 2.965 Zit.
Studies in health technology and informatics
2008 · 2.903 Zit.
Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success
2005 · 2.683 Zit.